Conditional estimation of exponential random graph models from snowball sampling designs

A complete survey of a network in a large population may be prohibitively difficult and costly. So it is important to estimate models for networks using data from various network sampling designs, such as link-tracing designs. We focus here on snowball sampling designs, designs in which the members of an initial sample of network members are asked to nominate their network partners, their network partners are then traced and asked to nominate their network partners, and so on. We assume an exponential random graph model (ERGM) of a particular parametric form and outline a conditional maximum likelihood estimation procedure for obtaining estimates of ERGM parameters. This procedure is intended to complement the likelihood approach developed by  Handcock and Gile (2010) by providing a practical means of estimation when the size of the complete network is unknown and/or the complete network is very large. We report the outcome of a simulation study with a known model designed to assess the impact of initial sample size, population size, and number of sampling waves on properties of the estimates. We conclude with a discussion of the potential applications and further developments of the approach.     

Are different affordances subserved by different neural pathways?

This paper questions whether affordances are allied exclusively to dorsal stream processing within the visual system, or whether in fact different affordances are subserved by functionally independent neural pathways. Using case study evidence from patients with various visual pathologies, I argue that affordances can be categorised into type based upon their respective neurological underpinning. Such categorisation has implications for the extent to which affordances are consciously perceived or non-consciously 'picked up' within the optic array, as well as whether they indicate merely potentials for action or provide necessary information in the actualisation of behaviour.     

Schizophrenia, ketamine and cannabis: evidence of overlapping memory deficits

Drug models of mental illness are considered useful if they provoke its characteristic symptoms. In this respect, ketamine and tetrahydrocannabinol (cannabis) are coming under increasing scrutiny as models for schizophrenia. However, although both undoubtedly produce psychotic symptoms characteristic of the disorder, we argue here that, because schizophrenia is also accompanied by cognitive deficits, a full understanding of the impact of these drugs on cognition will be crucial in taking these models further. Memory deficits are pronounced in schizophrenia and we focus upon patterns of working and episodic memory impairment produced by ketamine and cannabis, identifying overlaps between drug and illness. We suggest that close attention to these deficits can offer insights into core pathophysiology of schizophrenia.     

Analysis of proctor marking accuracy in a computer-aided personalized system of instruction course

In a computer-aided version of Keller's personalized system of instruction (CAPSI), students within a course were assigned by a computer to be proctors for tests. Archived data from a CAPSI-taught behavior modification course were analyzed to assess proctor accuracy in marking answers as correct or incorrect. Overall accuracy was increased by having each test marked independently by two proctors, and was higher on incorrect answers when the degree of incorrectness was larger.     

Predicting the relative efficacy of three presentation methods for assessing preferences of persons with developmental disabilities

Choices were presented to 9 individuals with developmental disabilities using a two-choice format. Each pair of items, selected based on prior preference assessment, was presented to each participant in three conditions (actual items, pictures of the items, and spoken-name presentation) using a reversal design. The evaluation was conducted using food items, and was then repeated using nonfood items. The participants were also given a test to measure their skills on discrimination tasks ranging in difficulty from simple to conditional discriminations. The participants' abilities to make consistent choices with food and nonfood items were predicted, with 94% accuracy, by their discrimination skills. The findings suggest that presentation methods can affect the accuracy of a choice assessment, and that the systematic assessment of basic discrimination skills can be used to predict the effectiveness of different presentation methods in this population.     

A few seemingly harmless routes to a false memory

Since the invention of photography we have learned to rely on photos to help us remember significant moments in our lives. We have come to believe that photographs are accurate and valuable records of events that—years down the track—we may not be able to remember. In this paper, we review recent research demonstrating that photographs can also help us to “remember” events that never really happened. We trace the development of the leading false autobiographical memory paradigm, and we then describe research on the power of both fake narrative stories and fake photographs to cultivate false memories.     

Network models for social influence processes

This paper generalizes thep* class of models for social network data to predict individual-level attributes from network ties. Thep* model for social networks permits the modeling of social relationships in terms of particular local relational or network configurations. In this paper we present methods for modeling attribute measures in terms of network ties, and so constructp* models for the patterns of social influence within a network. Attribute variables are included in a directed dependence graph and the Hammersley-Clifford theorem is employed to derive probability models whose parameters can be estimated using maximum pseudo-likelihood. The models are compared to existing network effects models. They can be interpreted in terms of public or private social influence phenomena within groups. The models are illustrated by an empirical example involving a training course, with trainees' reactions to aspects of the course found to relate to those of their network partners.This research was supported by grants from the Australian Research Council. The authors would like to acknowledge the help of Stanley Wasserman, Janice Langan-Fox and Larry Hubert, and would like to thank four anonymous reviewers for their helpful comments. Earlier versions of this article were presented at the North American Conference of the Psychometric Society, Lawrence, Kansas, June, 1999, and at the Australasian Mathematical Psychology Conference, Brisbane, Australia, December 1999.